Makine Mühendisliği Bölümü

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Citation - WoS: 2
Citation - Scopus: 3
On the Stability of Inverse Dynamics Control of Flexible-Joint Parallel Manipulators in the Presence of Modeling Error and Disturbances
(Tubitak Scientific & Technological Research Council Turkey, 2019) Korkmaz, Ozan; Denizli, Mustafa Semih; Ider, Sitki Kemal
Inverse dynamics control is considered for flexible-joint parallel manipulators in order to obtain a good trajectory tracking performance in the case of modeling error and disturbances. It is known that, in the absence of modeling error and disturbance, inverse dynamics control leads to linear fourth-order error dynamics, which is asymptotically stable if the feedback gains are chosen to make the real part of the eigenvalues of the system negative. However, when there are modeling errors and disturbances, a linear time-varying error dynamics is obtained whose stability is not assured only by keeping the real parts of the frozen-time eigenvalues of the system negative. In this paper, the stability of such systems is investigated and it is proved that the linear time-varying system can be rendered stable by selecting the feedback gains such that the variation of the system becomes sufficiently slow. To illustrate the performance of the control method, deployment motion of a 3-(R) under bar PR planar parallel manipulator subject to impact is simulated. For the impact model, the impulse-momentum and the coefficient of restitution equations for the system are derived.
Citation - WoS: 2
Citation - Scopus: 2
Parametric Analysis of an Anti-Whiplash System Composed of a Seat Suspension Arrangement
(Springer Heidelberg, 2015) Ider, Sitki Kemal; Gokler, Mustafa Ilhan; Ozdemir, Mustafa
Neck injuries frequently seen in low-speed rear-end collisions are referred to as whiplash injuries. Most of the proposed anti-whiplash systems in the literature rely on reducing the backset. A relatively new and promising alternative concept is a slideable seat. This study aimed to parametrically analyze an anti-whiplash vehicle seat that can slide backward against a horizontal suspension arrangement composed of a spring and a damper in response to a rear-end collision, and to investigate the effects of the suspension parameters on the injury risk. A simplified model of a slideable vehicle seat is developed, and simulations are conducted in LS-DYNA (R) environment using this slideable seat model and the commercially available finite element model of the BioRID II dummy. The maximum value of the Neck Injury Criterion (NICmax) is used as the measure of the injury risk. As a result, a strong linear inverse correlation is observed between NICmax and the maximum seat sliding distance, while the stiffness and damping coefficients of the suspension are varied. This result is also verified by obtaining the same NICmax value for the same maximum seat sliding distance (although the stiffness and damping coefficients are different). It is also shown that, for a given backset value as large as 60 mm, a slideable seat with the suspension parameters selected to yield a reasonable maximum seat sliding distance such as 100 mm significantly improves NICmax compared to a standard seat. As the maximum seat sliding distance is increased, the injury risk becomes smaller.
Citation - WoS: 2
Citation - Scopus: 1
Exploring the Potential of Artificial Intelligence Tools in Enhancing the Performance of an Inline Pipe Turbine
(Sage Publications Ltd, 2024) Celebioglu, Kutay; Ayli, Ece; Cetinturk, Huseyin; Tascioglu, Yigit; Aradag, Selin
In this study, investigations were conducted using computational fluid dynamics (CFD) to assess the applicability of a Francis-type water turbine within a pipe. The objective of the study is to determine the feasibility of implementing a turbine within a pipe and enhance its performance values within the operating range. The turbine within the pipe occupies significantly less space in hydroelectric power plants since a spiral casing is not used to distribute the flow to stationary vanes. Consequently, production and assembly costs can be reduced. Hence, there is a broad scope for application, particularly in small and medium-scale hydroelectric power plants. According to the results, the efficiency value increases on average by approximately 1.5% compared to conventional design, and it operates with higher efficiencies over a wider flow rate range. In the second part of the study, machine learning was employed for the efficiency prediction of an inline-type turbine. An appropriate Artificial Neural Network (ANN) architecture was initially obtained, with the Bayesian Regularization training algorithm proving to be the best approach for this type of problem. When the suitable ANN architecture was utilized, the prediction was found to be in good agreement with CFD, with an root mean squared error value of 0.194. An R2 value of 0.99631 was achieved with the appropriate ANN architecture.
Citation - Scopus: 4
Fused Filament Fabrication in Cad Education: a Closed-Loop Approach
(Sage Publications inc, 2025) Totuk, Onat Halis; Selvi, Ozguen; Akar, Samet
Integrating low-cost fused filament fabrication 3D printing as a foundation for learning 3D modelling is explored. This method blends traditional computer aided design (CAD) instruction with additive manufacturing possibilities. Experimental results demonstrate increased comprehension speed and reduced learning time. This hands-on approach empowers students by enabling direct engagement with the modelling process. Analogous to reverse engineering, the strategy instructs engineering students from final product to model creation, closing the gap between theory and practice. Incorporating 3D printing bridges this divide, enhancing understanding, creativity and problem-solving. The study underscores technology's influence on learning strategies, aligning with the surge of 3D printing in education. Results link advanced design technology usage to improved student performance, with 3D-printed materials yielding 45% higher grades and 30% faster task completion. This study advocates curricular advancement for design-focused careers through enhanced technology integration and favourable 3D printing model reception.
Citation - WoS: 1
Citation - Scopus: 1
Kinematic Analysis of Overconstrained Manipulators With Partial Subspaces Using Decomposition Method
(Cambridge Univ Press, 2022) Selvi, Ozgun
Overconstrained manipulators in lower subspaces with unique motions can be created and analyzed. However, far too little attention has been paid to creating a generic method for overconstrained manipulators kinematic analysis. This study aimed to evaluate a generic methodology for kinematic analysis of overconstrained parallel manipulators with partial subspaces (OPM-PS) using decomposition to parallel manipulators (PMs) in lower subspaces. The theoretical dimensions of the method are depicted, and the use of partial subspace for overconstrained manipulators is portrayed. The methodology for the decomposition method is described and exemplified by designing and evaluating the method to two overconstrained manipulators with 5 degrees of freedom (DoF) and 3 DoF. The inverse kinematic analysis is detailed with position analysis and Jacobian along with the inverse velocity analysis. The workspace analysis for the manipulators using the methodology is elaborated with numerical results. The results of the study show that OPM-PS can be decomposed into PMs with lower subspace numbers. As imaginary joints are being utilized in the proposed methodology, it will create additional data to consider in the design process of the manipulators. Thus, it becomes more beneficial in design scenarios that include workspace as an objective.
Citation - WoS: 20
Citation - Scopus: 20
Modeling of Mixed Convection in an Enclosure Using Multiple Regression, Artificial Neural Network, and Adaptive Neuro-Fuzzy Interface System Models
(Sage Publications Ltd, 2020) Ayli, Ece
In this study, the heat transfer characteristics of laminar combined forced convection through a horizontal duct are obtained with the help of the numerical methods. The effect of the geometrical parameters of the cavity and Reynolds number on the heat transfer is investigated. New heat transfer correlation for hydrodynamically fully developed, laminar combined forced convection through a horizontal duct is proposed with an average error of 6.98% and R-2 of 0.8625. The obtained correlation results are compared with the artificial neural network and adaptive neuro-fuzzy interface system models. Due to the obtained results, good agreement is identified between the numerical results and predicted adaptive neuro-fuzzy interface system results. In conclusion, it is seen that adaptive neuro-fuzzy interface system can predict the Nusselt number distribution with a higher accuracy than the developed correlation and the artificial neural network model. The developed adaptive neuro-fuzzy interface system model predicts the Nusselt number with 1.07% mean average percentage error and 0.9983 R-2 value. The effect of the different training algorithms and their ability to predict Nusselt number distribution are examined. According to the results, the Bayesian regulation algorithm gives the best approach with a 2.235% error. According to the examination that is performed in this study, the adaptive neuro-fuzzy interface system is a powerful, robust tool that can be used with confidence for predicting the thermal performance.
Citation - WoS: 6
Citation - Scopus: 6
Machine Learning Based Developing Flow Control Technique Over Circular Cylinders
(Asme, 2023) Turkoglu, Hasmet; Ayli, Ece; Kocak, Eyup
This paper demonstrates the feasibility of blowing and suction for flow control based on the computational fluid dynamics (CFD) simulations at a low Reynolds number flows. The effects of blowing and suction position, and the blowing and suction mass flowrate, and on the flow control are presented in this paper. The optimal conditions for suppressing the wake of the cylinder are investigated by examining the flow separation and the near wake region; analyzing the aerodynamic force (lift and drag) fluctuations using the fast Fourier transform (FFT) to separate the effects of small-scale turbulent structures in the wake region. A method for stochastic analysis using machine learning techniques is proposed. Three different novel machine learning methods were applied to CFD results to predict the variation in drag coefficient due to the vortex shedding. Although, the prediction power of all the methods utilized is in the acceptable accuracy range, the Gaussian process regression (GPR) method is more accurate with an R-2(coefficient of determination) > 0.95. The results indicate that by optimizing the blowing and suction parameters like mass flowrate, slot location, and the slot configuration, up to 20% reduction can be achieved in the drag coefficient.
Citation - WoS: 17
Citation - Scopus: 20
Experimental Investigation of Flow and Heat Transfer in Rectangular Cross-Sectioned Duct With Baffles Mounted on the Bottom Surface With Different Inclination Angles
(Springer, 2014) Onur, Nevzat; Arslan, Kamil
In this study, steady-state forced convection heat transfer and pressure drop characteristics in a horizontal rectangular cross-sectioned duct, baffles mounted on the bottom surface with different inclination angles were investigated experimentally in the Reynolds number range from 1 x 10(3) to 1 x 10(4). The study was performed under turbulent flow conditions. Effects of different baffle inclination angles on flow and heat transfer were studied. Results are also presented in terms of thermal enhancement factor. It is observed that increasing in baffle inclination angle enhances the heat transfer and causes an increase in pressure drop in the duct.
Citation - WoS: 1
Citation - Scopus: 1
Performance Determination of Axial Wind Tunnel Fan With Reverse Engineering, Numerical and Experimental Methods
(Asme, 2022) Ayli, Ece; Kocak, Eyup
In today's technology, in case of the need for rehabilitation, renovation, or damage, it is necessary to recover the problems quickly with a cost-effective approach. In the case of destructive failure, or misdesign of the devices, replacing the problematic part with the new design is crucial. In order to substitute the related part with the efficient one, reverse engineering (RE) methodology is utilized. In this paper, from the perspective of engineering implementation and based on the idea of reverse engineering, axial wind tunnel fan is rehabilitated using numerical and experimental methods. The current study is focused on an axial pressurization fan placed into Cankaya University Mechanical Engineering Laboratory wind tunnel that has firm guaranteed specifications of 5.55 m(3)/s airflow capacity. The measurements performed during experiments showed that the fan provides less than 60% airflow compared with firm guaranteed specifications. In order to determine the problems of the existing fan, a reverse engineering methodology is developed, and the noncontact data acquisition method is used to form a computer aided drawing (CAD) model. A computational fluid dynamics (CFD) methodology is developed to analyze existing geometry numerically, and results are compared with an experimental study to verify numerical methodology. According to the results, the prediction accuracy of the numerical method can attain 92.95% and 96.38% for flowrate and efficiency, respectively, at the maximum error points.
Citation - WoS: 3
Citation - Scopus: 3
A Comparative Study of Effects of Additive Particle Size and Content on Wetting Behavior and Brazing Performance of C/Sic Composite
(Springer, 2023) Esen, Ziya; Dericioglu, Arcan F.; Saltik, Simge
This study has focused on the influence of size and content of SiC particle incorporation on the wetting behavior of the Ticusil brazing filler alloy and on its brazing performance in C/SiC composite/Ti6Al4V alloy joints. The effect of the size and content of additive SiC particles on the variation of molten brazing filler alloy contact angle was recorded at various brazing time and temperatures. Moreover, the microstructural evolution and mechanical properties of the additive containing C/SiC composite/Ti6Al4V alloy joints produced by the brazing method were investigated. The contact angles in both brazing filler alloys containing nano- and micro-sized SiC particles exhibited a sudden decrease with time during isothermal holding as observed in as-received brazing filler alloys. As the quantity of the SiC particles increased in the brazing alloy, the recorded contact angle values including the final, stable contact angle increased, while the time for the drastic contact angle change also increased remarkably. Compared to as-received counterparts, the addition of 2 wt.% nano-sized SiC and 1 wt.% micro-sized SiC particles improved the shear strength of the joints by 35 and 8%, respectively. Although the recorded contact angle values were close to each other in brazing alloys containing SiC particles with different sizes (37 and 42 degrees for 1 wt.% micro-sized and 2 wt.% nano-sized additions), higher increment was achieved in the mechanical performance of the joints with nano-sized SiC additive due to more homogeneous reinforcement effect of the nanoparticles. The results indicated that the optimum brazing filler alloy contact angle for the highest shear strength is similar to 40 degrees for both nano- and micron-sized additive containing Ticusil filler alloy.
Citation - WoS: 9
Citation - Scopus: 11
Analysis of Heat Transfer Enhancement of Passive Methods in Tubes With Machine Learning
(Sage Publications Ltd, 2024) Ayli, Ece; Turkoglu, Hasmet; Yapici, Ekin Ozgirgin
This study investigates the efficacy of machine learning techniques and correlation methods for predicting heat transfer performance in a dimpled tube under varying flow conditions, including the presence of nanoparticles. A comprehensive numerical analysis involving 120 cases was conducted to obtain Nusselt numbers and friction factors, considering different dimple depths and velocities for both pure water and water-Al2O3 nanofluid at 1%, 2%, and 3% volume concentrations. Utilizing the data acquired from the numerical simulations, a correlation equation, SVM ANN architectures were developed. The predictive capabilities of the statistical approach, ANN, and SVM models for Nusselt number distribution and friction factor were meticulously assessed through mean average percentage error (MAPE) and correlation coefficients (R2). The research findings reveal that machine learning techniques offer a highly effective approach for accurately predicting heat transfer performance in a dimpled tube, with results closely aligned with Computational Fluid Dynamics (CFD) simulations. Particularly noteworthy is the superior performance of the ANN model, demonstrating the most precise predictions with an error rate of 2.54% and an impressive R2 value of 0.9978 for Nusselt number prediction. In comparison, the regression model achieved an average error rate of 6.14% with an R2 value of 0.8623, and the SVM model yielded an RMSE value of 2.984% with an R2 value of 0.9154 for Nusselt number prediction. These outcomes underscore the ANN model's ability to effectively capture complex patterns within the data, resulting in highly accurate predictions. In conclusion, this research showcases the promising potential of machine learning techniques in accurately forecasting heat transfer performance in dimpled tubes. The developed ANN model exhibits notable superiority in predicting Nusselt numbers, making it a valuable tool for enhancing thermal system analyses and engineering design optimization.
Citation - WoS: 3
Citation - Scopus: 4
Experimental and Numerical Investigation of Comparability of Whiplash Sled Test Results
(Springer Heidelberg, 2016) Ider, Sitki Kemal; Gokler, Mustafa Ilhan; Ozdemir, Mustafa
Whiplash-associated neck injuries represent an important health and socioeconomic problem attracting more and more attention of the vehicle safety community. Sled tests are conducted for the dynamic whiplash assessment of seats. However, reproducibility of the initial backset distances and of the sled pulses in every test plays an important role on the comparability of these results. In this study, in order to investigate these aspects, three different driver seat types are considered with three identical and unused samples for each of them, and by strictly following the European New Car Assessment Program (Euro NCAP) whiplash protocol and using the BioRID II dummy, totally nine sled tests are performed. The sled pulses are in general reproduced quite well for different vehicle seats in these tests. However, it is seen that there are differences of up to 5 mm in the initial backset distances recorded for the identical seats of the same type, while this difference increases up to 7 mm among the different seat types considered. Moreover, taking into account the associated tolerances allowed in this protocol, this uncertainty in the backset can even increase up to 10 mm. Based on the previous simulation results obtained by using the finite element model of the BioRID II dummy, linear regression models are constructed, and it is shown that a 10-mm increase in the backset will yield an increase of 2.25, 2.89 and 3.11 m(2)/s(2) in the NICmax values for the low, medium and high severity Euro NCAP pulses, respectively. Being 38, 22 and 31 % of the differences between the associated Euro NCAP higher and lower performance limits, and 68, 96 and 124 % of the differences between the associated Euro NCAP lower performance and capping limits, such increases in the NICmax values are found to bring an unacceptably high uncertainty in the test results, and they can even easily lead to the application of capping, which means giving a zero score for the entire test. In light of these findings, several suggestions are recommended for a more solid whiplash dynamic assessment procedure.
Citation - WoS: 8
Citation - Scopus: 10
Solar Chimney Power Plant Performance for Different Seasons Under Varying Solar Irradiance and Temperature Distribution
(Asme, 2021) Tareq, Maisarh; Ozgirgin, Ekin; Ayli, Ulku Ece
One of the most promising renewable energy sources is solar energy due to low cost and low harmful emissions, and from the 1980s, one of the most beneficial applications of solar energy is the utilization of solar chimney power plants (SCPP). Recently, with the advancement in computer technology, the use of computational fluid dynamics (CFD) methodology for studying SCPP has become an extensive, robust, and powerful technique. In light of the above, in this study, numerical simulations of an SCPP through three-dimensional axisymmetric modeling is performed. A numerical model is created using CFD software, and the results are verified with an experimental study from the literature. The amount of solar radiation and surrounding weather (ambient temperature) were analyzed, and the effects of the irradiance and air temperature on the output power of the SCPP were studied. Ambient temperature is considered as one of the most important factors that influence collector efficiency in a negative or a positive manner. Solar irradiance is considered to be the most important factor that has an impact on SCPP performance. The investigation includes the study of the relationship between solar insolation and ambient temperatures during the daytime since the difference between the minimum and maximum power values and the performance are very important considering seasonal changes. According to the results, power values are dependent on the amount of solar radiation as well as the ambient temperature, and the importance of selection of location thus climate for an SCPP is found to affect the design of the SCPP.
Citation - WoS: 4
Citation - Scopus: 4
Critical Decision Making for Rehabilitation of Hydroelectric Power Plants
(Taylor & Francis inc, 2023) Westerman, Jerry; Celebioglu, Kutay; Ayli, Ece; Ulucak, Oguzhan; Aradag, Selin
Due to their diminishing performance, reliability, and maintenance requirements, there has been a rise in the demand for the restoration and renovation of old hydroelectric power facilities in recent decades. Prior to initiating a rehabilitation program, it is crucial to establish a comprehensive understanding of the power plant's current state. Failure to do so may result in unnecessary expenses with minimal or no improvements. This article presents a systematic rehabilitation methodology specifically tailored for Francis turbines, encompassing a methodological approach for condition assessment, performance testing, and evaluation of rehabilitation potential using site measurements and CFD analysis, and a comprehensive decision-making process. To evaluate the off-design performance of the turbines, a series of simulations are conducted for 40 different flow rate and head combinations, generating a hill chart for comprehensive evaluation. Various parameters that significantly impact the critical decision-making process are thoroughly investigated. The validity of the reverse engineering-based CFD methodology is verified, demonstrating a minor difference of 0.41% and 0.40% in efficiency and power, respectively, between the RE runner and actual runner CFD results. The optimal efficiency point is determined at a flow rate of 35.035 m(3)/s, achieving an efficiency of 94.07%, while the design point exhibits an efficiency of 93.27% with a flow rate of 38.6 m(3)/s. Cavitation is observed in the turbine runner, occupying 27% of the blade suction area at 110% loading. The developed rehabilitation methodology equips decision-makers with essential information to prioritize key issues and determine whether a full-scale or component-based rehabilitation program is necessary. By following this systematic approach, hydroelectric power plants can efficiently address the challenges associated with aging Francis turbines and optimize their rehabilitation efforts.
Modeling and Optimization of a Peano-Hasel Actuator Peristaltic Pump
(Natl inst Science Communication-niscair, 2023) Mistikoglu, Selcuk; Totuk, Onat Halis
Peano-Hasel (hydraulically amplified self-healing electrostatic) pumps are crucial devices with unique mechanisms and versatile applications. They simulate muscle contractions to move fluids or materials through tubes. The Peano-Hasel method, a specific design, achieves flow by compressing a segmented tube externally. Exploring the design aspects of Peano-Hasel pumps can lead to advancements in optimizing their performance, efficiency, reliability, and control systems. This paper presents a novel method of peristaltic pumping on soft pipes using Peano-HASEL actuators. In the study, a design evaluation of an external ring-type pump over a PDMS (Polydimethylsiloxane -commonly referred to as silicone) tube containing Newtonian fluids is made, and a novel multi-pouch ring shape design is proposed. Our method utilizes a peripheral and compact design that allows for more efficient sinusoidal pumping action. The close proximity of the rings in the longitudinal direction enhances the effectiveness of the pumping process. The actuator is analytically modeled and optimized for maximum areal contraction and flow rate using a differential evolution algorithm. A MATLAB Simulink Simscape model is generated, and the system is simulated. As a result, an optimal solution for the number of pouches was found to be eight, considering ring geometry and applicability. It was also seen from the simulation that a sinusoidal squeezing scheme of a ring-type pump creates the desired action. Based on the analytical model presented, it has been demonstrated that the optimal flow rate is achieved when there are eight pouches, and they are fully circular after being energized.
Citation - WoS: 6
Citation - Scopus: 11
Modeling of Computer Virus Propagation With Fuzzy Parameters
(Tech Science Press, 2023) Ahmed, Nauman; Baleanu, Dumitru; Fatima, Umbreen; Dayan, Fazal; Rafiq, Muhammad; Mahmoud, Emad E.; Alhebshi, Reemah M.
Typically, a computer has infectivity as soon as it is infected. It is a reality that no antivirus programming can identify and eliminate all kinds of viruses, suggesting that infections would persevere on the Internet. To understand the dynamics of the virus propagation in a better way, a computer virus spread model with fuzzy parameters is presented in this work. It is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity, which depends on the quantity of virus. Considering this, the parameters beta and gamma being functions of the computer virus load, are considered fuzzy numbers. Using fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical models. The essential features of the model, like reproduction number and equilibrium analysis, are discussed in fuzzy senses. Moreover, with fuzziness, two numerical methods, the forward Euler technique, and a nonstandard finite difference (NSFD) scheme, respectively, are developed and analyzed. In the evidence of the numerical simulations, the proposed NSFD method preserves the main features of the dynamic system. It can be considered a reliable tool to predict such types of solutions.
Citation - WoS: 16
Citation - Scopus: 18
Electrostatic Energy Harvesting by Droplet-Based Multi-Phase Microfluidics
(Springer Heidelberg, 2012) Kulah, Haluk; Yildirim, Ender
This paper presents an energy scavenging technique, merging microfluidics with electrostatic energy harvesting. The method employs droplet-based microflow of two phases with different electrical permittivities, resulting in a capacitance change across the microchannel, to harvest electrical energy. The technique is implemented on 3 mm wide, 1 mm deep minichannels. It is shown that 0.4 nW can be harvested using a single electrode pair, with air and water as the two phases flowing at 1 ml/min. The generated power can be increased significantly by microscale implementation, where the number of electrodes can also be increased for further improvement.
Citation - WoS: 7
Citation - Scopus: 7
A Study on the Μwire-Edm of Ni55.8ti Shape Memory Superalloy: an Experimental Investigation and a Hybrid Ann/Pso Approach for Optimization
(Springer Heidelberg, 2023) Seyedzavvar, Mirsadegh; Boga, Cem; Akar, Samet
The unique properties of high hardness, toughness, strain hardening, and development of strain-induced martensite of nickel-titanium superalloys made the micro-wire electro discharge machining (mu wire-EDM) process one of the main practical options to cut such alloys in micro-scale. This paper presents the results of a comprehensive study to address the response variables of Ni55.8Ti superalloy in mu wire-EDM process, including the kerf width (KW), material removal rate (MRR), arithmetic mean surface roughness (R-a) and white layer thickness (WLT). To this aim, the effects of pulse on-time (T-on), pulse off-time (T-off), discharge current (I-d) and servo voltage (SV) as input parameters were investigated using the experiments conducted based on Taguchi L-27 orthogonal array. The results were employed in the analysis of variance (ANOVA) to examine the significance of input parameters and their interactions with the output variables. An optimization approach was adopted based on a hybrid neural network/particle swarm optimization (ANN/PSO) technique. The ANN was employed to achieve the models representing the correlation between the input parameters and output variables of the mu wire-EDM process. The weight and bias factor matrices were obtained by ANN in MATLAB and together with the feed forward/backpropagation model and developed functions based on PSO methodology were used to optimize the input parameters to achieve the minimum quantities of KW, R-a and WLT and the maximum value of MRR, individually and in an accumulative approach. The results represented a maximum accumulative error of nearly 8% that indicated the precision of the developed model and the reliability of the optimization approach. At the optimized level of input parameters obtained through the accumulative optimization approach, the KW, R-a, and WLT remained nearly intact as compared with the levels of responses obtained in the individual optimization approach, while there was a sacrifice in the machining efficiency and reduction in the MRR in the mu wire-EDM process of Nitinol superalloy.
Citation - WoS: 7
Citation - Scopus: 9
An Experimental Work on Using Conductive Powder-Filled Polymer Composite Cast Material as Tool Electrode in Edm
(Springer London Ltd, 2014) Cogun, Can; Yaman, Kemal
This paper introduces the composite tool electrodes made of electrical conductive powder-filled polyester resin matrix material, providing promise for the electrical discharge machining (EDM) process. The dendrite-shaped copper powder, graphite powder, and their mixture were used as conductive fillers. Six different types of composite electrodes, namely, plain copper-polyester, pressed copper-polyester, furnaced copper-polyester, plain copper-graphite-polyester, pressed copper-graphite-polyester, and furnaced copper-graphite-polyester were prepared. It is found experimentally that increasing v (f) improved workpiece material removal rate, tool wear rate, relative wear, and electrical conductivity of electrodes. The pressed copper-polyester electrodes were found to be promising in the ED finishing of workpieces at low machining current settings. The practical applicability of the proposed composite electrodes in the industry was also illustrated.
Molecular dynamic approach to predict thermo-mechanical properties of poly(butylene terephthalate)/CaCO3 nanocomposites
(2021) Seyedzavvar, Mirsadegh; Boğa, Cem; Akar, Samet; Pashmforoush, Farzad
Thermo-mechanical properties of poly(butylene terephthalate) polymer reinforced with carbonate calcium nanoparticles have been investigated using molecular dynamics simulations. Detailed analyses have been conducted on the effects of nanofiller content, at concentration levels of 0–7 wt%, on the mechanical properties of PBT, i.e. Young's modulus, Poisson's ratio and shear modulus. Thermal properties, including thermal conductivity and glass transition temperature, have been determined using Perl scripts developed based on nonequilibrium molecular dynamics and a high temperature annealing procedure, respectively. Experiments have been performed to verify the accuracy of the results of MD simulations. The CaCO3/PBT nanocomposites were synthesized using melt blending and mold injection techniques. The uniaxial tensile test, thermal conductivity, differential scanning calorimetry and x-ray diffraction spectroscopy measurements were conducted to quantify the thermo-mechanical properties of such nanocomposites experimentally. The results showed significant improvements in the mechanical properties by addition of CaCO3 nanoparticles due to strong binding between rigid particles and PBT polymer and high nucleation effects of nanoparticles on the matrix. Thermal conductivity and glass transition temperature of nanocomposites represented a consistent increase with the ratio of CaCO3 nanoparticles up to 5 wt% with an enhancement of 38% and 36% with respect to that of pure PBT, respectively. © 2021 Elsevier Ltd

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